Big Data and Machine Learning

Description

This area includes the distributed diagnosis and classification, large-scale semantic search, social networking analysis, and analysis of emotions and feelings.

Early research on machine learning in artificial systems date back to the 1950's. From the 80 start to develop practical applications of algorithms called "subsymbolic"(mainly Bayesian neural networks and systems) to problems of pattern recognitionand classification and the "symbolic" (induction of trees and rules) to knowledge acquisition for expert systems. In the 90 off with force what has been called 'data mining' application of learning algorithms and visualization for knowledge extractionin large databases. Our contributions in this field have also followed this path:

Application of Bayesian techniques for the assessment of risk in bank credit(ExpertBao project, 1986-1988).

Genetic algorithms and fuzzy logic to control power plants (ANOTHER project, 1989-1991) and in general for adaptive control of complex processes (projects courage andMITA).

Rodrigo Barbado. (2018). Design of a Prototype of a Big Data Analysis System of Online Radicalism based on Semantic and Deep Learning technologies. Final Career Project (TFM). Universidad Politécnica de Madrid, ETSIT, Madrid.

Rubén Jiménez. (2018). Design and implementation of a predictive module for the intrusion detection system snort based on supervised machine learning algorithms. Final Career Project (PFC). Universidad Politécnica de Madrid, ETSI Telecomunicación.

Manuel García-Amado. (2018). Development of a Fault Diagnosis System of Software Defined Networks based on Linked Data Technologies. Final Career Project (TFM). Universidad Politécnica de Madrid, ETSIT, Madrid.

Carlos Moreno-Sánchez. (2018). Design and Development of an Affect Analysis System for Football Matches in Twitter Based on a Corpus Annotated with a Crowdsourcing platform. Final Career Project (TFG). Universidad Politécnica de Madrid, ETSIT, Madrid.

José María Izquierdo-Mora. (2018). Design and Development of a Lyrics Emotion Analysis System for Creative Industries. Final Career Project (TFG). Universidad Politécnica de Madrid, ETSI Telecomunicación, Madrid.

Daniel Mata-Nieves. (2018). Development of a Real Time Classification System of Twitter Trends based on Machine Learning Techniques. Final Career Project (TFG). Universidad Politécnica de Madrid, ETSI Telecomunicación, Madrid.

Diego Benito-Sánchez. (2017). Design and Development of a Personality Traits Classifier based on Machine Learning Techniques. Final Career Project (TFG). ETSI Telecomunicación, Universidad Politécnica de Madrid.

Eduardo Varas. (2017). Design and Development of a Process Mining System for the Optimization of a Loan Approval Process. Final Career Project (TFG). ETSI Telecomunicación, Universidad Politécnica de Madrid.

Carlos Alonso Aguilar. (2017). Design and development of a Personality Prediction System based on Mobile-Phone based Metrics. Final Career Project (TFG). ETSI Telecomunicación, Universidad Politécnica de Madrid.

Álvaro Martínez-Carmena. (2017). Development of a Fault Diagnosis system based on Bayesian Networks for Software Defined Networks. Final Career Project. ETSI Telecomunicación, Universidad Politécnica de Madrid.

Rodrigo Barbado. (2016). Development of a Classification System of Deceptive Behaviours based on Machine Learning Techniques. Application to Fake Reviews and Radicalist Recruiters Detection. Final Career Project. ETSI Telecomunicación, Universidad Politécnica de Madrid.

Julián Amigó Francés. Development and Evaluation of a Sarcasm Detection Algorithm based on Machine Learning and Natural Language Processing Techniques. Final Career Project (TFG). Universidad Politécnica de Madrid, ETSI Telecomunicación.

Alberto Pascual-Saavedra. Development of a Big Data system for analysis and visualization of social media based on REST services.. Final Career Project (TFM). Universidad Politécnica de Madrid, ETSI Telecomunicación.